Very well-put, but I'd say that there is a slight difference between AI and ML, if just in scope: AI says "we want to make a program that thinks, and we can do it relatively soon", and ML says "there's this particular statistical classicification problem that we're trying to solve". ML may eventually lead to AI, but there's plenty of reasons to be skeptical about the few who advocate good ol'fashioned strong AI. (I'm aiming that towards Cyc/OpenCyc, Mindpixel, and Moravec, although I've lost track of what he's doing these days. The Cog project seems less grandiose and cocky to judge from their statements
.) But beyond all of that, different branches of ML, and also human cognitive modelling, are active, and chipping away at their own domain-specific problems.
"It's beat time, it's hop time, it's monk time!"